58 citations · 182 across the 22 of their papers we have counts for
4 papers · 1 filter
Densifying Sparse Representations for Passage Retrieval by Representational Slicing
Sheng-Chieh Lin, Jimmy Lin
Learned sparse and dense representations capture different successful approaches to text retrieval and the fusion of their results has proven to be more effective and robust. Prior…
Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling
Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang +2
A vital step towards the widespread adoption of neural retrieval models is their resource efficiency throughout the training, indexing and query workflows. The neural IR community…
Contextualized Query Embeddings for Conversational Search
Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin
This paper describes a compact and effective model for low-latency passage retrieval in conversational search based on learned dense representations. Prior to our work, the state-o…
Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin +3
Pyserini is an easy-to-use Python toolkit that supports replicable IR research by providing effective first-stage retrieval in a multi-stage ranking architecture. Our toolkit is se…